基于压缩感知理论的WSN微震源定位节点设计

提出了一种基于压缩感知的WSN微震源数据压缩算法.利用WSN微震信息的可稀疏化表示,设计出与稀疏基相关性低的稀疏观测矩阵,保证了压缩数据的可重构性,介绍了整个WSN微震源定位节点的系统设计,包括采集、存储以及无线传输方式等.将该压缩感知算法在硬件系统中实现,可利用较少的数据采集实现微震源定位,从而大大提高了存储、采集及WSN的效率.实验结果表明,该算法的硬件实现在保证微震信息完整性的基础上,数据压缩率达到60％,具有十分重要的研究意义.

WSN Microseismic Source Location Node Design Based on Compression Perception Theory

In the paper,a data compression algorithm for WSN microseismic source based on compressed sensing is proposed.Sparse representation of WSN microseismic information is used to design sparse observation matrix with low correlation between sparse bases,which ensures the reconfigurability of compressed data.The compressed sensing algorithm is implemented in the hardware module of WSN microseismic source location node system,which includes acquisition,storage and wireless transmission mode.The design is characterized by less data acquisition to achieve microseismic location,which greatly improves the efficiency of storage,collection and WSN.The experiment results show that the data compression rate of hardware implementation of this algorithm can reach 60％ on the basis of ensuring integrity of microseismic information,and has great significance to related research.